Ironman Maryland doesn’t seem to have much luck. Last year it was postponed resulting in lower competitor numbers, this year there race went ahead, but conditions forced the cancellation of the swim and the shortening of the bike. With a chunk of the race missing, age group times are naturally faster. We can’t really directly compare results with previous races, but I’ve run the analysis and plotted times and Kona slots as usual.

Obviously there are no swim splits this year which removes at least an hour from the overall time for most athletes. The bike course was reduced to 100 miles which would correspond well with the 30-40 minute faster times we see at this years race. That adds up to over 90 minutes off the overall splits too. The run course remained the full distance and there we see less change in splits.

DNS and DNF Rates at Ironman Maryland

Listed Athletes

Swim Finish

Swim DNS/DNF

Bike Finish

Bike DNS/DNF

Run Finish

Run DNF

Overall DNS/DNF

2014

1495

1447

3.2%

1433

1%

1378

3.8%

7.8%

2015

2613

1415

45.8%

1394

1.5%

1359

2.5%

48%

2016

2572

1964

24%

1886

4%

26.7%

In its first year we don’t have DNS data in the table, only staters are listed in the athlete count. In its second year a last minute change of race date resulted in a very high DNS rate. This year it’s hard to pick out as DNS and DNF rate are mixed into the bike numbers rather than the swim. It looks like DNS may have been slightly higher than usual after than changes. DNF rates on the run are up to, perhaps surprising given the shortened race.

There isn’t much to compare here given the huge differences in the races. No swim, a faster bike and a similar run.

Ironman Maryland 2016 Predicted Kona Qualifiers by Country

Country

Percentage of Slots

Percentage of Field

United States

75.0

83.5

Canada

7.5

3.7

Germany

5.0

0.5

Denmark

5.0

0.2

Costa Rica

2.5

1.1

France

2.5

0.7

The majority of slots went to the majority nations with a handful of others picking up a decent portion of places.

Top 10 Nationalities at Ironman Maryland

Count

Percentage

United States

2148

83.5

Canada

96

3.7

Mexico

33

1.3

Costa Rica

29

1.1

United Kingdom

22

0.9

Puerto Rico

21

0.8

France

19

0.7

Brazil

15

0.6

Colombia

13

0.5

Germany

12

0.5

As always with North American races the majority of athletes come from North America with a small number coming from further south or Europe.

Naturally the shortened course results in much faster times across age groups and positions for this year’s race.

Ironman Maryland 2016 Predicted Kona Qualification Times

Slots

Winner

Average Kona Qualifier

Final Qualifier

M18-24

1

7:17:40

7:17:40

7:17:40

M25-29

2

7:14:38

7:15:26

7:16:14

M30-34

2

6:59:24

7:01:45

7:04:06

M35-39

3

7:04:48

7:13:56

7:20:57

M40-44

3

7:13:55

7:19:05

7:26:11

M45-49

3

7:41:27

7:50:45

8:01:00

M50-54

3

7:56:52

8:05:09

8:10:21

M55-59

2

8:27:33

8:28:08

8:28:43

M60-64

1

8:59:10

8:59:10

8:59:10

M65-69

1

9:35:55

9:35:55

9:35:55

M70-74

1

10:45:02

10:45:02

10:45:02

M75-79

1

14:01:49

14:01:49

14:01:49

F18-24

1

8:46:33

8:46:33

8:46:33

F25-29

1

8:32:56

8:32:56

8:32:56

F30-34

2

8:23:54

8:25:25

8:26:57

F35-39

2

8:14:27

8:18:10

8:21:53

F40-44

2

8:25:20

8:43:36

9:01:52

F45-49

2

8:30:22

8:42:34

8:54:47

F50-54

2

9:00:22

9:11:36

9:22:51

F55-59

1

9:44:28

9:44:28

9:44:28

F60-64

1

11:04:07

11:04:07

11:04:07

F65-69

1

10:34:32

10:34:32

10:34:32

F70-74

1

13:59:02

13:59:02

13:59:02

The table above takes my Kona slot estimates (based on the athlete list) and calculates the automatic qualifying times for each age group. It doesn’t account for roll down or the number of people who didn’t make the start line. Obviously the times are fast on the shortened course, you can compare them with other races on my Kona qualification page.

And it’s not surprise to see this year’s top twenty age group times well ahead of the previous results and averages. There’s not much to comment on in the circumstances. When conditions force these changes to a race times are going to be much faster. In this case they seem to be broadly in line with performances on the full course in Maryland, but we can’t make a firm comparison.